University of Waterloo
Undergraduate Program in Data Science

Guidelines for Course Selection and Planning

Mu Zhu, PhD
Professor, Department of Statistics and Actuarial Science
Interim Director of Data Science, 2017–2018

Math faculty requirements: Communication skills requirements: Take one course from List I as usual; take MTHEL 300 from List II. Faculty core courses (Table II): Take one course from each of 10 categories as usual except that, if you must select CS 115 (rather than CS 135/145) and CS 116 (rather than CS 136/146), e.g., due to inadequate preparation, you must still take CS 136 afterwards (and use up one of your free electives); for the last category, take one of MATH 237/247 and one of MATH 239/249. Data science requirements: By following the guidelines above, you will have satisfied the first two requirements already (i.e., MATH 239/249 and CS 136/146). Simply follow the rest of the requirements here verbatim except that, for the last two requirements, replace with "one of CS 485/486" and "two of STAT 431/440/441/442/443/444". Honors statistics requirements: Data Science students must satisfy all requirements for the Honors Statistics program. By following the guidelines above, you will have satisfied all these requirements except "all of MTHEL 300, STAT 330/331/332/333", so simply take them all. Notes: Essentially, all the "additional math courses" demanded by the Honors Statistics program here―altogether 7 in total, out of which 4 must be 300- or 400-level―will have to become specific CS courses as required by the Data Science program above―specifically, "all of CS 240/241/245/246/251/341/348/350/451", altogether 9 in total. As a result, Honors Statistics students will have a minimum of 26 math courses, whereas Data Science students will have a minimum of 28. Data science program sheet: The course sequences recommended here have been checked to satisfy all the requirements above, as well as the requirement that students must also take a minimum of 10 non-math courses.